"""
汽车行业与数学研究综合程序(智能增强版)
主程序入口
"""

import sys
import logging
from typing import Dict, Any
from modules.automotive import (
    AutomotiveMarketAnalysis,
    AutomotiveTechnicalCalculations,
    AutomotiveCostAnalysis,
    AutomotiveSupplyChainAnalysis
)
from modules.math import MathematicalResearch
from agents.data_analysis_agent import AIDataAnalysisAgent
from agents.prediction_agent import PredictionModelAgent
from agents.optimization_agent import OptimizationAgent
from agents.interaction_agent import UserInteractionAgent

class Application:
    """主应用程序类"""
    
    def __init__(self):
        """初始化应用程序"""
        self._setup_logging()
        self.logger = logging.getLogger(__name__)
        
        # 初始化功能模块
        self.market = AutomotiveMarketAnalysis()
        self.tech = AutomotiveTechnicalCalculations()
        self.math = MathematicalResearch()
        self.cost = AutomotiveCostAnalysis()
        self.supply_chain = AutomotiveSupplyChainAnalysis()
        
        # 初始化智能体
        self.ai_agent = AIDataAnalysisAgent()
        self.pred_agent = PredictionModelAgent()
        self.opt_agent = OptimizationAgent()
        self.ui_agent = UserInteractionAgent()
        
        self.logger.info("应用程序初始化完成")
    
    def _setup_logging(self) -> None:
        """配置日志系统"""
        logging.basicConfig(
            level=logging.INFO,
            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
            handlers=[
                logging.FileHandler('app.log'),
                logging.StreamHandler(sys.stdout)
            ]
        )
    
    def run(self) -> None:
        """运行主程序"""
        try:
            self._show_welcome()
            self._main_loop()
        except KeyboardInterrupt:
            self.logger.info("用户中断程序")
            print("\n程序已退出")
        except Exception as e:
            self.logger.error(f"程序运行错误: {str(e)}")
            print(f"\n发生错误: {str(e)}")
    
    def _show_welcome(self) -> None:
        """显示欢迎信息"""
        print("\n" + "="*50)
        print("汽车行业与数学研究综合程序(智能增强版)")
        print("="*50)
        print("版本: 2.0")
        print("智能功能: 数据分析、预测建模、优化决策、自然语言交互")
        print("输入 'q' 退出程序\n")
    
    def _main_loop(self) -> None:
        """主循环"""
        while True:
            self._show_menu()
            choice = input("请输入选项(1-6, q退出): ").strip().lower()
            
            if choice == 'q':
                break
            
            self._handle_choice(choice)
    
    def _show_menu(self) -> None:
        """显示主菜单"""
        print("\n主菜单:")
        print("1. 汽车市场数据分析 - 分析市场趋势和销售数据")
        print("2. 汽车技术参数计算 - 计算技术规格和性能指标")
        print("3. 数学建模应用 - 应用数学模型解决行业问题")
        print("4. 汽车成本分析 - 分析制造成本和利润率")
        print("5. 汽车供应链分析 - 评估供应链效率和风险")
        print("6. 智能体技术支持 - 演示AI智能体功能")
        print("\n提示: 输入数字选择功能，输入'q'退出程序")
    
    def _handle_choice(self, choice: str) -> None:
        """处理用户选择"""
        handlers = {
            '1': self._handle_market_analysis,
            '2': self._handle_tech_calculations,
            '3': self._handle_math_applications,
            '4': self._handle_cost_analysis,
            '5': self._handle_supply_chain,
            '6': self._handle_ai_agents
        }
        
        handler = handlers.get(choice)
        if handler:
            handler()
        else:
            print("无效选项，请重新输入")
    
    def _handle_market_analysis(self) -> None:
        """处理市场分析选项"""
        print("\n汽车市场数据分析功能")
        # 实现市场分析逻辑...
    
    def _handle_ai_agents(self) -> None:
        """处理智能体技术选项"""
        print("\n智能体技术演示:")
        self._demo_ai_agents()
    
    def _demo_ai_agents(self) -> None:
        """演示智能体功能"""
        # 示例1: 智能数据分析
        sample_data = {
            'price': [20, 25, 30, 35, 40],
            'sales': [100, 120, 150, 130, 160]
        }
        print("\n[智能数据分析示例]")
        print("输入数据:", sample_data)
        analysis_result = self.ai_agent.auto_analyze(sample_data)
        print("分析结果:", analysis_result)
        
        # 示例2: 自然语言交互
        print("\n[自然语言交互示例]")
        query = "请分析最近的销售数据"
        print(f"用户查询: '{query}'")
        parsed_query = self.ui_agent.natural_language_query(query)
        print("解析结果:", parsed_query)
        
        # 示例3: 预测模型
        print("\n[预测模型示例]")
        X = [[1], [2], [3], [4], [5]]
        y = [2, 4, 6, 8, 10]
        print(f"训练数据 - X: {X}, y: {y}")
        model_result = self.pred_agent.train_predictive_model(X, y)
        print("模型训练结果:", model_result['metrics'])

if __name__ == "__main__":
    app = Application()
    app.run()